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diffusion models using path integral formulations. This project aims to advance quantum machine learning by: Designing a quantum counterpart of diffusion models; Leveraging path integral methods to model
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of Singapore’s maritime sector. The project focuses on developing planning methods to support the electrification of harbour craft fleets, using real-world operational data to derive charging demand profiles and
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to the terrestrial carbon cycle. Implement advanced statistical method to explore the vegetation dynamics. The formulation and testing of ecological hypotheses on vegetation dynamics. Presentation of results
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, TEM, XRD, AFM, XPS). Machine learning methods. High-throughput experiment design and data analysis. Scientific writing and communication. Data processing and visualization software (CrystalMaker
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Engineering Experience conducting empirical studies within the field of systems and software engineering Strong knowledge of qualitative research method (interviews, focus groups, case studies, grounded theory
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Health. As part of this collaboration, CRiHSP is hiring a highly motivated and experienced postdoctoral researcher to lead a research project employing mixed-methods for the development of methods
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applications and funding opportunities; Provide guidance and training to undergraduate/graduate students and junior researchers in laboratory techniques and research methods; Present research findings in
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Job Title: Postdoctoral Scholar (Digital fabrication of Sustainable Materials) Scope of the Research: This research program intends to develop design principles, fabrication methods, and instruments
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lead research on next-generation solar harvesting materials, focusing on developing and optimizing synthesis methods for novel inorganic nanoparticles and quantum dots designed for solar-to-energy
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Responsible for developing LC-MS method for structural elucidations of natural carbohydrates Perform chemical biology assays to evaluate the bioactivity of natural and synthetic carbohydrates Job Requirements